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- Tasks: Deliver innovative data science solutions and build custom forecasting models.
- Company: Join a dynamic consultancy focused on cutting-edge data-driven projects.
- Benefits: Enjoy flexible working options and a collaborative team culture.
- Why this job: Be part of exciting projects that make a real impact in the tech world.
- Qualifications: Strong background in data science, machine learning, and cloud technologies required.
- Other info: Ideal for those who thrive in fast-paced, agile environments.
The predicted salary is between 36000 - 60000 £ per year.
Key Responsibilities:
- Deliver end-to-end data science solutions in a consultancy environment
- Build and deploy custom forecasting models (e.g., time series, XGBoost, deep learning)
- Implement reinforcement learning techniques for dynamic prediction
- Apply causal inference and graph AI methods to uncover complex relationships
- Develop and containerize models using Docker
- Work within modern CI/CD pipelines to streamline deployment
- Operate in a cloud environment (AWS preferred)
- Contribute to the development of a data-driven web application using JavaScript/TypeScript and Next.js
Required Skills & Experience:
- Strong experience as a Full Stack Data Scientist
- Deep expertise in time series forecasting and machine learning (XGBoost, deep learning, reinforcement learning)
- Practical knowledge of Causal AI and Graph AI methodologies
- Proficiency in Python for data science and model development
- Experience with Docker, CI/CD workflows, and AWS
- Comfortable working with JavaScript, Next.js, and ideally TypeScript
- Ability to thrive in a consulting or agency environment with changing client demands
- Strong ownership of delivery and adaptability to fast-moving projects
Desirable:
- Experience in retail analytics
- Prior work in cross-functional teams building web-based data products
- Exposure to start-up style or agile project settings
Contract Data Scientist employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Contract Data Scientist
✨Tip Number 1
Familiarise yourself with the latest trends in data science, especially in areas like time series forecasting and reinforcement learning. This will not only help you during interviews but also demonstrate your passion for the field.
✨Tip Number 2
Build a portfolio showcasing your experience with Docker and CI/CD pipelines. Having practical examples of how you've containerised models or streamlined deployment processes can set you apart from other candidates.
✨Tip Number 3
Network with professionals in the data science community, particularly those who work in consultancy environments. Engaging in discussions about projects and challenges can provide insights and potentially lead to referrals.
✨Tip Number 4
Stay updated on cloud technologies, especially AWS, as well as JavaScript and Next.js. Being able to discuss your hands-on experience with these tools will show that you're ready to hit the ground running.
We think you need these skills to ace Contract Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience as a Full Stack Data Scientist. Emphasise your expertise in time series forecasting, machine learning techniques like XGBoost and deep learning, and any relevant projects that showcase your skills.
Craft a Compelling Cover Letter: In your cover letter, explain why you're interested in the Contract Data Scientist position. Mention specific experiences that align with the job responsibilities, such as building custom forecasting models or working with Docker and CI/CD pipelines.
Showcase Relevant Projects: If you have worked on projects involving causal inference, graph AI, or cloud environments (especially AWS), be sure to include these in your application. Provide links to your GitHub or portfolio if applicable.
Highlight Adaptability: Since the role requires thriving in a consultancy environment, mention any experiences where you've successfully adapted to changing client demands or worked in fast-paced settings. This will demonstrate your ability to handle the dynamic nature of the job.
How to prepare for a job interview at Harnham
✨Showcase Your Technical Skills
Be prepared to discuss your experience with data science tools and techniques, especially in time series forecasting, XGBoost, and deep learning. Bring examples of past projects where you've successfully implemented these methods.
✨Demonstrate Your Problem-Solving Ability
Consultancy roles often require quick thinking and adaptability. Prepare to discuss how you've tackled complex problems in the past, particularly using causal inference and graph AI methods.
✨Familiarise Yourself with CI/CD and Docker
Since the role involves deploying models using Docker and working within CI/CD pipelines, be ready to explain your experience with these technologies. Consider discussing a specific project where you utilised these tools effectively.
✨Understand the Consulting Environment
As this position requires thriving in a consultancy setting, think about how you've managed changing client demands in previous roles. Be ready to share examples that highlight your adaptability and ownership of delivery.
